{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5627eef3",
   "metadata": {},
   "source": [
    "## Hi\n",
    "\n",
    "This is some markdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3d8a9364",
   "metadata": {
    "tags": [
     "plot-line"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZGTNDgCmRhhSR77azoIi7Jy7k3aVb6Nu+EU/8qCsNTqgedCwJUCTH3GeZ2URgLlACzKPsMMs0YJyZPRxe9mJFBBWRQ5uzfjvDx84nb08h91/QkevPbKkPTSWy89zd/SHgoW8sXgP0iOR9ReTwQiHn2Y9X8+SMFTSrW5OJN51B1+Z1g44lUUInu4rEoLw9hdwxfgGfrdrKoC5N+O3FnaldQ7M5yn+p3EVizCcr8rljwnz2Hijh0Ys78+PuzXW1JPkfKneRGFFcGuIP767guY9X0y7lBF4f2pN2KbWCjiVRSuUuEgOytxcwfNw85m3YyRU90nhwUCdqVtNFq+XbqdxFotz0RbncPWkhOPzlylMZ1KVp0JEkBqjcRaJUYXEpD09byt9nbqBrah3+fEU30hokBx1LYoTKXSQKrcrbwy2vz2PZ5j0M692KX5zbnmpJugSeHDmVu0gUcXfemJPDQ1OWULNaVUZf152+7RsHHUtikMpdJErsPVDCfW8uYsr8TfRq1YA/Xn4KKbVrBB1LYpTKXSQKLMrZxa1j57JhewF3nNOOm/u20UyOEhGVu0iA3J3Rn6/jd9OzaHhCdcYN60WPlrpgtURO5S4SkB37irhr4gLey8qjf8cUHr+0C/WOrxZ0LIkTKneRAMxas43bxs1n+74iHvpBJ649I11TCEiFUrmLHEOlIecvH6zi6fdXkFY/mck/O4OTm9UJOpbEIZW7yDGyZXcht42bx8w127nwlKY8fFFnTqiuX0GpHPrJEjkGPlyex50TFrC/qJTHL+3Cpael6jCMVCqVu0glOlBSyhP/Ws7zn66lw4m1+MuV3WjT+ISgY0kCULmLVJI563dwz6SFrMrby//1TOP+CzpR4zjN5CjHhspdpIIVFJXw+L+W8/IX62hSu4amEJBAqNxFKtBnK7cyYvJCcnbs55peLbh7QAd9aCqBiOinzszqAi8AJwMOXA8sB8YD6cA64DJ33xHJekSi3a6CYh7551ImZObQsuHxTLhRI00lWJHuUjwNvOPul5pZNSAZGAm87+6PmtkIYARwT4TrEYla7yzezANTFrN9XxE/7dOa2/q11bF1CVy5y93M6gC9gWsB3L0IKDKzwUCf8NNeAT5C5S5xKH/PAX45dQnTFuXSqUltRl/bXQOSJGpEsufeEsgHRptZV2AOcBuQ4u654edsBlIO9WIzGwYMA0hLS4sghsix5e5MnruRX7+9lP1Fpdx1XnuG9W7FcVV1MQ2JHpGUexLQDbjV3WeZ2dOUHYL5D3d3M/NDvdjdRwGjADIyMg75HJFok7OjgPveXMzHK/I5rUU9Hruki85bl6gUSbnnADnuPit8fyJl5b7FzJq4e66ZNQHyIg0pErRQyPn7rPU8Nn0ZDvzyB524plc6VTTnukSpcpe7u282s2wza+/uy4F+wNLw1xDg0fD3KRWSVCQgq/P3MmLSQmav28H32zbktxd1pnl9XahaolukZ8vcCrwWPlNmDXAdUAWYYGY3AOuByyJch0ggiktDPP/pGv743kpqHleVJ37UlUu6NdOcMBITIip3d58PZBzioX6RvK9I0BZv3MU9kxayZNNuzj/5RH41+CQa19L1TCV2aOicyEEKi0v58wcree7jNdRLrsazV3Xj/M5Ngo4lctRU7iJhmeu2c/ekhazJ38elp6Vy/wUdqZusy95JbFK5S8Lbe6CEx99ZxpiZ62lapyZjru9B73aNgo4lEhGVuyS0j1fkM3LyIjbt2s+QXuncdV57jtdEXxIH9FMsCWlnQRG/eTuLSXNzaN3oeN64sRcZ6ZroS+KHyl0SzvRFuTwwZQk7Coq4pW8bbjm7jSb6krijcpeEkbe7kAenLOGdJZs5qWltXrm+Oyc11URfEp9U7hL33J035uTw8NtLKSwJcc+ADgz9fkuSNNGXxDGVu8S17O0FjHxzEZ+u3EqP9Pr87pLOtG6kib4k/qncJS6VlIYY8+V6nnh3OQb8ZvBJXHV6C030JQlD5S5xxd35aEU+j0zLYlXeXs5q14jfXtyZZnVrBh1N5JhSuUvcWLZ5N49My+LTlVtJb5DMqKtP45xOKZroSxKSyl1iXv6eAzw5YwXjZ2/ghOpJPDCoE1f3bEG1JH1gKolL5S4xq7C4lBc/W8tfP1zFgZIQQ85IZ/jZbal3vOaDEVG5S8xxd6Yu2MTv31nOxp37OadTCvee34FWOgtG5D9U7hJT5qzfwcPTljJvw046NanN4z/qwhmtGwYdSyTqqNwlJmRvL+Cxd5bx9sJcGteqzuOXduHibqlU1amNIoekcpeotruwmL9+uJqXPl9LFYPh/dpyY+9WmrlR5DD0GyJRqaQ0xLjZ2Tw1YwXb9hVxcbdm3HVee5rU0fnqIkdC5S5R5+MV+TwybSkrtuylR8v6jL6gI11S6wYdSySmRFzuZlYVyAQ2uvsgM2sJjAMaAHOAq929KNL1SPxbsWUPj0zL4uMV+bRokMxz/3ca552kQUgi5VERe+63AVlA7fD9x4Cn3H2cmT0H3AA8WwHrkTi1de8BnpqxgrFflQ1Cuv+CjlzTK12DkEQiEFG5m1kqcAHwCHCHle1inQ1cGX7KK8AvUbnLIRQWlzL683U88+EqCotLuaZXOrf10yAkkYoQ6Z77H4G7gVrh+w2Ane5eEr6fAzSLcB0SZ9ydtxfm8uj0ZWzcuZ/+HRtz78COmopXpAKVu9zNbBCQ5+5zzKxPOV4/DBgGkJaWVt4YEmPmbtjBw28vZe6GnXRsUpvfX9qFM9toEJJIRYtkz/1M4IdmNhCoQdkx96eBumaWFN57TwU2HurF7j4KGAWQkZHhEeSQGJCzo4Dfv7OcqQs20ahWdX5/SRcuOU2DkEQqS7nL3d3vBe4FCO+5/8LdrzKzN4BLKTtjZggwJfKYEqv2FBbz7EereeGz8CCks9tw41mtNQhJpJJVxm/YPcA4M3sYmAe8WAnrkChXUhpiQmYOT85Yzta9RVx8ajN+cV57muqiGSLHRIWUu7t/BHwUvr0G6FER7yux599XQnr0n8tYvmUP3dPr8dK13TUISeQY09/GUiFCIedfSzbzzEerWLxxN2n1k3n2qm4MOPlEDUISCYDKXSJSXBpiyvxNPPvRKlbn7yO9QTKPXdKZi05N1SAkkQCp3KVcCotLmZCZzd8+XsPGnfvpcGIt/nzFqQzs3ERnwIhEAZW7HJU9hcX8feYGXvxsDVv3FnFai3r85sKT6Nu+sQ6/iEQRlbscke37ihj9+Vpe+WIduwtL6N2uETf3aU2PlvVV6iJRSOUu3yl3136e/2QtY7/aQGFJKQNOOpGf9WlD59Q6QUcTke+gcpdDWrt1H3/7eDWT5uYQcrjwlGb8tE8r2jSudfgXi0jgVO7yNVm5u/nrR6uZtnATSVWrcEWPNIZ+vxXN6ycHHU1EjoLKXQCYs347z3y4mg+W5XFC9SSG9W7N9d9Lp3GtGkFHE5FyULknMHfn05VbeebDVcxau516ycfxi3PbcXWvdOrUPC7oeCISAZV7AgqFnHeXbuaZD1ezaOMuTqxdgwcHdeLyHs1JrqYfCZF4oN/kBFJcGmLq/E08+/FqVuXt/c9o0gtPbUb1pKpBxxORCqRyTwCFxaW8kZnNcxpNKpIwVO5xbE9hMa/N2sALn65l694DdEurq9GkIglC5R6Htu8r4uXP1/JyeDTp99s25Oa+p3K6RpOKJAyVexzZuHM/L322ltdnbWB/cXg0ad/WmktdJAGp3GNcUUmID5ZtYdzsbD5ekU8VM40mFRGVe6xalbeXCZnZTJqTw7Z9RTSpU4Nb+7bhsu7NSa2n0aQiiU7lHkMKikqYtjCXCZnZzF63g6QqRv+OKfy4R3N6t22kM19E5D9U7lHO3Vm0cRfjZmczdf4m9h4ooVWj4xk5sAMXnZpKo1rVg44oIlFI5R6ldhYU8da8jYybnc2yzXuocVwVBnVpyo+7NyejRT2d9SIi36nc5W5mzYExQArgwCh3f9rM6gPjgXRgHXCZu++IPGr8C4WcmWu2MW52Nu8s2UxRSYguqXV45KKT+UHXptSuofleROTIRLLnXgLc6e5zzawWMMfMZgDXAu+7+6NmNgIYAdwTedT4tXlXIRPnZDMhM4cN2wuoXSOJK3ukcVlGczo1rR10PBGJQeUud3fPBXLDt/eYWRbQDBgM9Ak/7RXgI1Tu/6O4NMSHy/IYPzubD5fnEXI4o3UD7jy3HeeddCI1jtNcLyJSfhVyzN3M0oFTgVlASrj4ATZTdtjmUK8ZBgwDSEtLq4gYMWHt1n2Mn53NxDk5bN17gMa1qvPTPq25LKM5LRocH3Q8EYkTEZe7mZ0ATAJ+7u67D/6gz93dzPxQr3P3UcAogIyMjEM+J17sLypl+uJcxs/OZtba7VStYvRt35jLuzenT/tGJFWtEnREEYkzEZW7mR1HWbG/5u6Tw4u3mFkTd881syZAXqQhY9XijbsYPzubt+ZvZE9hCS0aJHP3gPZc2i2VxrV1hSMRqTyRnC1jwItAlrs/edBDU4EhwKPh71MiShhjdu0vZur8slMYl2zaTfWkKgzs3ITLMprTs5Um7hKRYyOSPfczgauBRWY2P7xsJGWlPsHMbgDWA5dFlDAGuDtfrd3O+NnZTFuUy4GSEJ2a1ObXg09icNdm1EnWKYwicmxFcrbMZ8C37Yb2K+/7xorC4lK+XL2NGVlbeD9rC1t2H6BW9SR+lJHK5d3TOLlZnaAjikgC0wjVo5C/5wAfLsvjvawtfLpyK/uLSzm+WlV6t2vEuSelMOCkJtSsplMYRSR4Kvfv4O6szNvLjKVle+fzsnfiDk3r1OBHGan065hCz1b1df1REYk6KvdvKC4NMXvtdmZkbeG9rC1kb98PQJfUOtzevx39OjamU5Pa+mBURKKayh3YVVDMRyvyeC8rj4+W57GnsITqSVU4s01DfnpWG/p1bEyKTl0UkRiSsOW+ftu+8OGWPL5at53SkNPwhGoMPLkJ/To25nttG5JcLWE3j4jEuIRpr9KQMz97BzOWln0guipvLwDtU2px01mt6N8xha6pdamiC16ISByI63Lfd6CET1fm815WHh8sy2P7viKSqhint6rPVaen0b9jCs3r65J0IhJ/4q7cc3ft572sPN7P2sIXq7ZRVBqido0kzu7QmH4dUzirfSPNiy4icS/my93dWbJpNzOWlp3dsmTTbgDSGyRzTa8W9OuYQkZ6PY7T5FwikkBiutw/WLaFkZMXs3l3IVUMuqXVY8T5HejfMYXWjY7X6YoikrBiutyb1KnJKc3r0r9TCn3bN6LBCbpYtIgIxHi5d2xSm+euPi3oGCIiUUcHokVE4pDKXUQkDqncRUTikMpdRCQOqdxFROKQyl1EJA6p3EVE4pDKXUQkDpm7B50BM8sH1gedI0INga1Bh4gi2h5fp+3xX9oWXxfJ9mjh7o0O9UBUlHs8MLNMd88IOke00Pb4Om2P/9K2+LrK2h46LCMiEodU7iIicUjlXnFGBR0gymh7fJ22x39pW3xdpWwPHXMXEYlD2nMXEYlDKncRkTikcq8gZlbVzOaZ2dtBZwmSmdU1s4lmtszMssysV9CZgmRmt5vZEjNbbGZjzaxG0JmOJTN7yczyzGzxQcvqm9kMM1sZ/l4vyIzH0rdsj8fDvy8LzexNM6tbEetSuVec24CsoENEgaeBd9y9A9CVBN4mZtYMGA5kuPvJQFXg8mBTHXMvAwO+sWwE8L67twXeD99PFC/zv9tjBnCyu3cBVgD3VsSKVO4VwMxSgQuAF4LOEiQzqwP0Bl4EcPcid98ZaKjgJQE1zSwJSAY2BZznmHL3T4Dt31g8GHglfPsV4MJjmSlIh9oe7v6uu5eE784EUitiXSr3ivFH4G4gFHCOoLUE8oHR4UNUL5jZ8UGHCoq7bwSeADYAucAud3832FRRIcXdc8O3NwMpQYaJMtcD0yvijVTuETKzQUCeu88JOksUSAK6Ac+6+6nAPhLrT+6vCR9LHkzZf3pNgePN7P+CTRVdvOxcbJ2PDZjZfUAJ8FpFvJ/KPXJnAj80s3XAOOBsM/t7sJECkwPkuPus8P2JlJV9ouoPrHX3fHcvBiYDZwScKRpsMbMmAOHveQHnCZyZXQsMAq7yChp8pHKPkLvf6+6p7p5O2YdlH7h7Qu6duftmINvM2ocX9QOWBhgpaBuAnmaWbGZG2fZI2A+YDzIVGBK+PQSYEmCWwJnZAMoO6/7Q3Qsq6n2TKuqNRMJuBV4zs2rAGuC6gPMExt1nmdlEYC5lf27PI8GG3pvZWKAP0NDMcoCHgEeBCWZ2A2VTfV8WXMJj61u2x71AdWBG2T4AM939pojXpekHRETijw7LiIjEIZW7iEgcUrmLiMQhlbuISBxSuYuIxCGVu4hIHFK5i4jEof8HJHv2C7M1Q4YAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "x=[3,4,5,6,7,8,9,10,11,12]\n",
    "y= [9,16,25,36,49,64,81,100,121,144]\n",
    "plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "176f6946",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#| label: plot-dot\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "x=[3,4,5,6,7,8,9,10,11,12]\n",
    "y= [9,16,25,36,49,64,81,100,121,144]\n",
    "plt.scatter(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ff7727fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "x=[4,9,16,25,36]\n",
    "fig = plt.figure(figsize =(9, 5)) # line 4\n",
    "plt.pie(x)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9b3f7a5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 396x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "x=[4,9,16,25,36]\n",
    "fig = plt.figure(figsize =(5.5, 5.5))\n",
    "plt.pie(x, labels=(\"Guavas\", \"Berries\",\"Mangoes\",\"Apples\", \"Avocado\"),\n",
    "colors = ( \"#a86544\", \"#eb5b13\", \"#ebc713\", \"#bdeb13\", \"#8aeb13\"))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "471ab83a-6593-42ca-8945-f5217037e120",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
